I. Climate Change

1. What Causes Flash Floods in the Middle East?

Researchers zero in on the large-scale meteorological processes driving extreme precipitation events in the hot, arid desert region.

https://eos.org/research-spotlights/what-causes-flash-floods-in-the-middle-east

2. Images Suggest a Viral Role in Some Rock Formation

Viruses might have helped transform dense bacterial colonies into a type of sedimentary rock that is frequently associated with underground oil reserves.

https://eos.org/articles/images-suggest-a-viral-role-in-some-rock-formation

3. Diversity of El Niño Variability Makes Prediction Challenging

The atmospheric response to El Niño, both in the Pacific region and around the world, changes with each event and is uncertain in future under the influence greenhouse gas forcing.

https://eos.org/editors-vox/diversity-of-el-nino-variability-makes-prediction-challenging

4. Nordic Workshop Takes on Major Puzzles of Paleomagnetism

8th Nordic Paleomagnetism Workshop; Leirubakki, Iceland, 30 September to 7 October 2017

https://eos.org/meeting-reports/nordic-workshop-takes-on-major-puzzles-of-paleomagnetism

II. Hazards & Disasters

1. Evidence for Gravity Tectonics After the Great Sumatra Quake

A new method that applies structural geology principles to aftershock analyses suggests that gravity-driven motion may occur during part of the seismic cycle.

https://eos.org/research-spotlights/evidence-for-gravity-tectonics-after-the-great-sumatra-quake

2. Satellites and Cell Phones Form a Cholera Early-Warning System

A new initiative combines satellite data with ground observations to assess and predict the risk of cholera outbreaks in Bangladesh’s vulnerable populations.

https://eos.org/project-updates/satellites-and-cell-phones-form-a-cholera-early-warning-system

III. Ocean Sciences

1. Advancing Satellite Ocean Color Observations

A new derived algorithm for particle backscattering and multi-year VIIRS climatology improves ocean color parameterization in highly turbid coastal and inland waters.

https://eos.org/editor-highlights/advancing-satellite-ocean-color-observations

2. Pacific’s Garbage Hot Spot Holds More Plastic Debris Than Was Thought

A nonprofit that helped to collect data for the research plans to use the study’s findings to help guide it in an upcoming campaign to remove buoyant plastic trash from ocean gyres.

https://eos.org/articles/pacifics-garbage-hot-spot-holds-more-plastic-debris-than-was-thought

IV. Biogeosciences

1. The Upside to a “Bad” Ozone Precursor

In Sweden’s wet heathland, scientists see how a sensitive ecosystem adapts to rising global temperatures.

https://eos.org/research-spotlights/the-upside-to-a-bad-ozone-precursor

2. Winter Conditions Are Changing Rapidly in Alpine Lake Ecosystems

LimnoAlp Workshop; Lake Cadagno, Switzerland, 10–15 September 2017

https://eos.org/meeting-reports/winter-conditions-are-changing-rapidly-in-alpine-lake-ecosystems

V. Geology & Geophysics

1. The Big Picture in Geospace

A NASA stereo-imaging mission called TWINS continues to push the boundaries of what we know about the region of space close to Earth.

https://eos.org/editors-vox/the-big-picture-in-geospace

2. Radon Tells Unexpected Tales of Mount Etna’s Unrest

Readings from a sensor for the radioactive gas near summit craters of the Italian volcano reveal signatures of such processes as seismic rock fracturing and sloshing of groundwater and other fluids.

https://eos.org/project-updates/radon-tells-unexpected-tales-of-mount-etnas-unrest

VI. Geophysical Research Letters

1. Framing Climate Goals in Terms of Cumulative CO2‐Forcing‐Equivalent Emissions

The relationship between cumulative CO2 emissions and CO2‐induced warming is determined by the Transient Climate Response to Emissions (TCRE), but total anthropogenic warming also depends on non‐CO2 forcing, complicating the interpretation of emissions budgets based on CO2 alone. An alternative is to frame emissions budgets in terms of CO2‐forcing‐equivalent (CO2‐fe) emissions—the CO2 emissions that would yield a given total anthropogenic radiative forcing pathway. Unlike conventional “CO2‐equivalent” emissions, these are directly related to warming by the TCRE and need to fall to zero to stabilize warming: hence, CO2‐fe emissions generalize the concept of a cumulative carbon budget to multigas scenarios. Cumulative CO2‐fe emissions from 1870 to 2015 inclusive are found to be 2,900 ± 600 GtCO2‐fe, increasing at a rate of 67 ± 9.5 GtCO2‐fe/yr. A TCRE range of 0.8–2.5°C per 1,000 GtC implies a total budget for 0.6°C of additional warming above the present decade of 880–2,750 GtCO2‐fe, with 1,290 GtCO2‐fe implied by the Coupled Model Intercomparison Project Phase 5 median response, corresponding to 19 years' CO2‐fe emissions at the current rate.

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017GL076173

2. Collapse of the 2017 Winter Beaufort High: A Response to Thinning Sea Ice?

The winter Arctic atmosphere is under the influence of two very different circulation systems: extratropical cyclones travel along the primary North Atlantic storm track from Iceland toward the eastern Arctic, while the western Arctic is characterized by a quasi‐stationary region of high pressure known as the Beaufort High. The winter (January through March) of 2017 featured an anomalous reversal of the normally anticyclonic surface winds and sea ice motion in the western Arctic. This reversal can be traced to a collapse of the Beaufort High as the result of the intrusion of low‐pressure systems from the North Atlantic, along the East Siberian Coast, into the Arctic Basin. Thin sea ice as the result of an extremely warm autumn (October through December) of 2016 contributed to the formation of an anomalous thermal low over the Barents Sea that, along with a northward shift of the tropospheric polar vortex, permitted this intrusion. The collapse of the Beaufort High during the winter of 2017 was associated with simultaneous 2‐sigma sea level pressure, surface wind, and sea ice circulation anomalies in the western Arctic. As the Arctic sea ice continues to thin, such reversals may become more common and impact ocean circulation, sea ice, and biology.

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017GL076446

3. Dynamical Core in Atmospheric Model Does Matter in the Simulation of Arctic Climate

Climate models using different dynamical cores can simulate significantly different winter Arctic climates even if equipped with virtually the same physics schemes. Current climate simulated by the global climate model using cubed‐sphere grid with spectral element method (SE core) exhibited significantly warmer Arctic surface air temperature compared to that using latitude‐longitude grid with finite volume method core. Compared to the finite volume method core, SE core simulated additional adiabatic warming in the Arctic lower atmosphere, and this was consistent with the eddy‐forced secondary circulation. Downward longwave radiation further enhanced Arctic near‐surface warming with a higher surface air temperature of about 1.9 K. Furthermore, in the atmospheric response to the reduced sea ice conditions with the same physical settings, only the SE core showed a robust cooling response over North America. We emphasize that special attention is needed in selecting the dynamical core of climate models in the simulation of the Arctic climate and associated teleconnection patterns.

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017GL076092

4. A Possible Link Between Winter Arctic Sea Ice Decline and a Collapse of the Beaufort High?

A new study by Moore et al. (2018, https://doi.org/10.1002/2017GL076446) highlights a collapse of the anticyclonic “Beaufort High” atmospheric circulation over the western Arctic Ocean in the winter of 2017 and an associated reversal of the sea ice drift through the southern Beaufort Sea (eastward instead of the predominantly westward circulation). The authors linked this to the loss of sea ice in the Barents Sea, anomalous warming over the region, and the intrusion of low‐pressure cyclones along the eastern Arctic. In this commentary we discuss the significance of this observation, the challenges associated with understanding these possible linkages, and some of the alternative hypotheses surrounding the impacts of winter Arctic sea ice loss.

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2018GL077704

5. A deep‐learning algorithm of neural network for the parameterization of typhoon–ocean feedback in typhoon forecast models

Two algorithms based on machine‐learning neural networks are proposed—the shallow learning (S‐L) and deep learning (D‐L) algorithms—that can potentially be used in atmosphere‐only typhoon forecast models to provide flow‐dependent typhoon‐induced sea surface temperature cooling (SSTC) for improving typhoon predictions. The major challenge of existing SSTC algorithms in forecast models is how to accurately predict SSTC induced by an upcoming typhoon, which requires information not only from historical data, but more importantly also from the target typhoon itself. The S‐L algorithm composes of a single layer of neurons with mixed atmospheric and oceanic factors. Such a structure is found to be unable to represent correctly the physical typhoon‐ocean interaction. It tends to produce an unstable SSTC distribution, for which any perturbations may lead to changes in both SSTC pattern and strength. The D‐L algorithm extends the neural network to a 4 × 5 neuron matrix with atmospheric and oceanic factors being separated in different layers of neurons, so that the machine learning can determine the roles of atmospheric and oceanic factors in shaping the SSTC. Therefore, it produces a stable crescent‐shaped SSTC distribution, with its large‐scale pattern determined mainly by atmospheric factors (e.g. winds) and small‐scale features by oceanic factors (e.g. eddies). Sensitivity experiments reveal that the D‐L algorithms improve maximum wind intensity errors by 60% ~ 70% for 4 case study simulations, compared to their atmosphere‐only model runs.

https://agupubs.onlinelibrary.wiley.com/doi/10.1002/2018GL077004

VII. AGU Blogs

1. Underway CTD’s: The struggle is ‘reel’

Although our expensive new robots can cruise underwater for days at a time, setting them up for their most scientifically valuable missions begins with compiling data to form a picture of the oceanic feature we are trying to study. Satellite altimetry shows us differences of tens of centimeters above or below the average sea surface height, which are usually indicators of eddy features. Crossing a suspected eddy using an Acoustic Doppler Current Profiler (ADCP) uncovers the ocean current speed and direction from the surface to over 100 meters deep. While the ADCP shows the spinning motion, a preferable study site also includes the vertical motion of water masses. Visualizing vertical shifts in salinity and temperature across sections of eddy’s hundreds of kilometers wide is the specialty of the underway CTD (uCTD).

https://blogs.agu.org/thefield/2018/03/27/underway-ctds-the-struggle-is-reel/

2. The Marjorie – Reclaiming #FloridaWoman for the Florida environment [Women’s History Month]

Having lived in Florida for six years while attending the University of Miami-RSMAS for my Ph.D., I’ll always have a place for “The Sunshine State” in my heart. I spent countless hours not only in the lab but outdoors in the Florida Keys, Everglades National Park, and Biscayne Bay. One of my first course-based fieldtrips was in a Carbonate Sedimentology course taught by Dr. Robert Ginsburg.

https://blogs.agu.org/geoedtrek/2018/03/26/the-majorie/

3. You can help compile the NASA landslide catalogue

For the last few years Dalia Kirschbaum and colleagues have been compiling a NASA landslide catalogue, with a focus on rainfall-induced landslides, to help with their work on landslide climatology.  In a move that we should all welcome, this dataset has now been placed online and can be accessed via a web-based GIS application.  The is an incredibly helpful and powerful tool, both for understanding the nature and distribution of the hazard and for teaching.  There are a range of different ways to plot the data, allowing the user to tailor the analysis to his or her needs.

https://blogs.agu.org/landslideblog/2018/03/27/nasa-landslide-catalogue-1/

4. Building a scicomm program from the salt marsh up

As a scientist whose research required lying face-down in muddy salt marshes to search for itty-bitty marine snail eggs, I was often asked by casual onlookers, “Why the heck are you doing THAT?”

https://blogs.agu.org/sciencecommunication/2018/03/26/8816/